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Vertex Block Descent

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arxiv 2403.06321 v4 pith:3WQBANNS submitted 2024-03-10 cs.GR

Vertex Block Descent

classification cs.GR
keywords blockdescentvertexachievecomputationconvergencemethodstability
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We introduce vertex block descent, a block coordinate descent solution for the variational form of implicit Euler through vertex-level Gauss-Seidel iterations. It operates with local vertex position updates that achieve reductions in global variational energy with maximized parallelism. This forms a physics solver that can achieve numerical convergence with unconditional stability and exceptional computation performance. It can also fit in a given computation budget by simply limiting the iteration count while maintaining its stability and superior convergence rate. We present and evaluate our method in the context of elastic body dynamics, providing details of all essential components and showing that it outperforms alternative techniques. In addition, we discuss and show examples of how our method can be used for other simulation systems, including particle-based simulations and rigid bodies.

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Cited by 1 Pith paper

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    Isaac Lab is a unified GPU-native platform combining high-fidelity physics, photorealistic rendering, multi-frequency sensors, domain randomization, and learning pipelines for scalable multi-modal robot policy training.